My solutions for many various coding/algorithmic problems (this repo will be updated with new solutions from time to time).
All solutions are written in Python (more precisely, Python 3), using the Built-in Functions and few modules from the Python Standard Library like:

• math (used for constants like math.pi, math.inf and functions like math.ceil, math.floor, math.gcd, math.log, math.pow, math.sqrt, etc)
• collections (used for collections.deque when there is a need for Stack or Queue data structures)
• heapq (used when there is a need for Priority Queue data structure).

So, to execute these solutions there is no need from installing any external packages.
Coding style and name conventions are described in this file PEP8.
These problems are from sites like LeetCode (you can find more than 30 sites like this in the Training Sites section).
Also in this README you can find many resources for learning algorithms: Courses, Books, Training Sites, Other Resources.

Each solution/problem in this repo belongs to one of these categories:

1. Strings
2. Lists
3. Linked Lists
4. Trees
5. Dynamic Programming
6. Backtracking
7. Graphs
8. Math
9. Other

Each file with solution in this repo will have the following template:

'''
Problem name

Problem explanation

Input: XXX
Output: XXX
Output explanation: XXX

=========================================
Solution explanation
	Time Complexity: 	O(X)
	Space Complexity: 	O(X)
Solution 2 explanation
(some of the problems are solved in more than one way)
	Time Complexity: 	O(X)
	Space Complexity: 	O(X)
'''

############
# Solution #
############

def name_of_problem(params):
    # description of code
    pass

##############
# Solution 2 #
##############

def name_of_problem_2(params):
    # description of code
    pass


###########
# Testing #
###########

# Test 1
# Correct result => 'result'
print(name_of_problem('example'))

# Test 2
# Correct result => 'result2'
print(name_of_problem_2('example2'))

Collection of free courses from one of the best CS universities.

1. Princeton University (Coursera)

   • Algorithms Part 1
   • Algorithms Part 2

2. Standford University (Coursera)

   • Divide and Conquer, Sorting and Searching, and Randomized Algorithms
   • Graph Search, Shortest Paths, and Data Structures
   • Greedy Algorithms, Minimum Spanning Trees, and Dynamic Programming
   • Shortest Paths Revisited, NP-Complete Problems and What To Do About Them

3. MIT University (YouTube)

   • Introduction to algorithms 2005
   • Introduction to algorithms 2011 - 6.006
   • Design and analysis of algorithms - 6.046J
   • Advanced Data Structures - 6.851

4. Harvard University (YouTube)

   • Advanced algorithms - CS224

5. UC Berkeley

   • Data Structures - CS61B
   • Efficient Algorithms and Intractable Problems - CS170

Several books that have made an impression on me:

1. Grokking Algorithms by Aditya Bhargava - The best book for complete beginners in algorithms! I wish this book existed when I started learning algorithms.
2. Introduction to Algorithms by Thomas H. Cormen
3. Algorithms by Robert Sedgewick & Kevin Wayne
4. The Algorithm Design Manual by Steven Skiena

1. Geeks For Geeks - The site which all interested in algorithms (no matter if beginners or experts) should know!
2. The Algorithms - Python - Great GitHub repo with many algorithms written in Python.
3. KhanAcademy - Algorithms - Good explanations for some basic algorithms.
4. HackerRank - YouTube tutorials
   • Algorithms
   • Data Structures

If the problems from LeetCode are not enough and you need more problems like those, you can find much more on these platforms:

• HackerRank
• CodeChef
• HackerEarth
• CodeForces
• Topcoder
• Project Euler
• Codility
• CoderByte
• CodingBat
• CodeAbbey
• Wolfram Challenges
• CS Academy
• Daily Coding Problem
• Daily Interview Pro
• Codewars
• SPOJ
• Online Judge
• LintCode
• DevPost
• USA CO
• CodeFu
• Mendo
• Kattis
• AlgoExpert
• Brilliant
• Kaggle
• Codingame
• CheckiO
• Rosalind
• CodeKata
• FightCode